AI Architect — Ship to Production

Review Model Metrics & Experiment Logs

Architecture Decision Record (ADR)

Read AI/ML Paper or Blog Post

Team Sync / Technical Design Review

Cost & Latency Budget Check

Deep Focus / No-Meeting Block (2+ hours)

Ship AI Feature to Production

• Define success metrics and evaluation criteria
• Complete baseline model and benchmark against requirements
• Build data pipeline and feature store integration
• Pass staging environment load testing and safety review
• Production deployment with monitoring and rollback plan
• Post-launch 2-week performance report and iteration plan

Establish AI Governance & Best Practices

• Document model card and data lineage for primary model
• Implement automated bias and fairness checks in CI/CD
• Create prompt/model versioning and A/B test framework
• Publish internal AI architecture guidelines for the team

AI Project Kickoff

• Audit available training data for quality and coverage
• Select model framework and hosting infrastructure
• Set up experiment tracking (MLflow / Weights & Biases)
• Define API contract between model service and consumers
• Establish cost budget and alert thresholds for inference
• Schedule weekly demo with stakeholders